Principal Embedded Edge AI Engineer
Listed on 2026-05-23
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Engineering
AI Engineer (Applied/Software) -
IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Who we are
Johnson Controls is a global leader in smart, healthy, and sustainable buildings. Our mission is to reimagine the performance of buildings to serve people, places, and the planet. We support a multitude of industries across the globe and offer meaningful work projects and learning opportunities.
What We Offer- Competitive salary
- Paid vacation/holidays/sick time
- Comprehensive benefits package including 401K, medical, dental, and vision care
- On‑the‑job/cross‑training opportunities
- Encouraging and collaborative team environment
- Dedication to safety through our Zero Harm policy
As a Principal Embedded Edge AI Engineer on the Data Center Cooling Optimization team, you will design and deploy advanced AI/ML models—including LLM/SLM‑style architectures—directly onto embedded and edge platforms that control mission‑critical cooling systems. This role requires deep technical expertise and will involve working at the intersection of data science, embedded software, and real‑time control, developing time‑series intelligence, anomaly detection, and predictive maintenance models that operate under strict latency, compute, and reliability constraints.
You will guide system‑level decisions across software, controls, and hardware teams.
This position is 100% on‑site at our new Controls Product Development Center and Lab in Glendale, WI, with up to 20% travel.
How you will do it- Develop & deploy AI/ML on embedded and edge devices
- Build time‑series models for load estimation, anomaly detection, and RUL/condition‑based maintenance
- Implement Tensor Flow or PyTorch models optimized for edge execution
- Develop embedded inference pipelines in C/C++ (Rust a plus)
- Collaborate with data scientists to translate research models into production‑ready embedded implementations
- Work with IoT and controls teams to integrate ML outputs into real‑time control loops
- Optimize models for latency, memory footprint, and power constraints
- Apply FMEA, SFMEA, and PHM principles to ensure reliability and safety
- Lead system‑level debugging, validation, and performance tuning
- Mentor engineers and influence technical direction across the organization
Required Qualifications
- Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, or related field
- 4+ years of experience in embedded AI/ML, edge inference, or related fields
- Strong background in time‑series ML and deep learning architectures
- Proficiency with Tensor Flow or Py Torch
- Strong C/C++ skills for embedded or performance‑critical paths
- Experience deploying ML models on edge devices or embedded systems
- Familiarity with reliability engineering (FMEA, PHM)
- Ability to work under minimal supervision and guide technical decisions
- Excellent communication and cross‑functional collaboration skills
- Experience with digital twins and reinforcement learning for control
- Experience with LLM/SLM‑style architectures optimized for edge
- Experience with IoT protocols and edge compute frameworks
- Experience with data‑center systems, HVAC, or thermal management
- Rust programming experience
- Experience with model compression, quantization, or hardware acceleration
Salary range: $110,000 - $164,000. Compensation is based on education, experience, skills, and market data. The role offers a competitive bonus plan and benefits. For more detail on hiring practices, you may visit the Careers site.
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